NUMERICAL LINEAR ALGEBRA FOR HIGH-PERFORMANCE COMPUTERS

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NUMERICAL LINEAR ALGEBRA FOR HIGH-PERFORMANCE COMPUTERS

This book presents a unified treatment of recently developed techniques and current understanding about solving systems of linear equations and large scale eigenvalue problems on high-performance computers. It provides a rapid introduction to the world of vector and parallel processing for these linear algebra applications. Topics include major elements of advanced-architecture computers and their performance, recent algorithmic development, and software for direct solution of dense matrix problems, direct solution of sparse systems of equations, iterative solution of sparse systems of equations, and solution of large sparse eigenvalue problems.

This book supersedes the SIAM publication Solving Linear Systems on Vector and Shared Memory Computers, which appeared in 1990. The new book includes a considerable amount of new material in addition to incorporating a substantial revision of existing text. About the Authors: Jack J. Dongarra is a Distinguished Professor of Computer Science at the University of Tennessee and a Distinguished Scientist at Oak Ridge National Laboratory. Iain S. Duff is Group Leader of Numerical Analysis at the CCLRC Rutherford Appleton Laboratory, the Project Leader for the Parallel Algorithms Group at CERFACS in Toulouse, and a Visiting Professor of Mathematics at the University of Strathclyde. Danny C. Sorensen is a Professor of Computational and Applied Mathematics at Rice University. Henk A. van der Vorst is a Professor in Numerical Analysis at Utrecht University in the Netherlands.

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